Optimizing Surgical Capacity for a Rural Hospital Through Monte Carlo Simulation

Area of Science:

• Healthcare Management
• Operations Research
• Health Systems Engineering

Background:

• Rural hospitals face challenges in optimizing operating room (OR) utilization.
• Limited resources and data analytics capabilities can hinder efficiency improvements.

Purpose of the Study:

• To apply Monte Carlo simulation for evaluating and enhancing OR utilization in a small rural hospital.
• To identify key factors influencing OR capacity and implement data-driven process improvements.

Main Methods:

• Utilized Monte Carlo simulation with input factors including procedure duration, operational days, and shift length.
• Collected and analyzed real-time data on OR utilization to inform simulation parameters.
• Implemented changes based on simulation findings to improve OR workflow.

Main Results:

• Achieved a 38% increase in the number of procedures completed.
• Successfully created additional capacity for future growth and new service offerings.
• Established a sustainable model for ongoing data collection and analysis of OR utilization.

Conclusions:

• Rural hospitals can effectively use available data and simulation techniques to improve OR process flow.
• Partnerships with educational institutions can overcome limitations in in-house analytic resources.
• The implemented model demonstrates the potential for significant efficiency gains in rural healthcare settings.